Engines generating strong uniformly distributed pseudo-random numbers;
Needed by all JET probability distributions since they rely on uniform random numbers to generate random numbers from their own distribution.

DistinctNumberList
Resizable compressed list holding numbers; based on the fact that a number from a large list with few distinct values need not take more than log(distinctValues) bits; implemented with a MinMaxNumberList.

MinMaxNumberList
Resizable compressed list holding numbers; based on the fact that a value in a given interval need not take more than log(max-min+1) bits; implemented with a cern.colt.bitvector.BitVector.

HyperGeometric
HyperGeometric distribution; See the math definition
The hypergeometric distribution with parameters N, n and s is the probability distribution of the random variable X,
whose value is the number of successes in a sample of n items from a population of size N that has s 'success' items and N - s 'failure' items.

RandomSampler
Space and time efficiently computes a sorted Simple Random Sample Without Replacement (SRSWOR), that is, a sorted set of n random numbers from an interval of N numbers;
Example: Computing n=3 random numbers from the interval [1,50] may yield the sorted random set (7,13,47).

class

RandomSamplingAssistant
Conveniently computes a stable Simple Random Sample Without Replacement (SRSWOR) subsequence of n elements from a given input sequence of N elements;
Example: Computing a sublist of n=3 random elements from a list (1,...,50) may yield the sublist (7,13,47).

MightyStaticBin1D
Static and the same as its superclass, except that it can do more: Additionally computes moments of arbitrary integer order, harmonic mean, geometric mean, etc.

class

QuantileBin1D
1-dimensional non-rebinnable bin holding double elements with scalable quantile operations defined upon;
Using little main memory, quickly computes approximate quantiles over very large data sequences with and even without a-priori knowledge of the number of elements to be filled;
Conceptually a strongly lossily compressed multiset (or bag);
Guarantees to respect the worst case approximation error specified upon instance construction.